Background
Breast cancer (BRCA) is one of the most frequent malignant tumors in women worldwide. Lysosomes are known to regulate tumor cell proliferation by manipulating growth factor signaling and providing nutrition. However, the role of lysosomes and lysosome-related genes (LRGs) in BRCA is yet unclear. Therefore, this study aimed to identify the lysosomal-related biomarkers for predicting the prognosis and immunotherapeutic response of BRCA.
Results
Based on the expression of 15 prognostic LRGs, BRCA cases were divided into two subtypes with significantly different overall survival (OS). In all, 537 differentially expressed lysosome-related genes (DELRGs) were identified and they were significantly enriched in the PI3K-Akt signaling pathway, protein digestion and absorption, and regulation of actin cytoskeleton. Then, the risk model was constructed based on five biomarkers, namely, QPRT, EIF4EBP1, IGJ, UGDH, and IL1R1. The Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves revealed that the risk model could accurately predict the prognosis of BRCA cases, and age, stage, and risk score were regarded as independent prognostic indicators. According to Gene set enrichment analysis (GSEA), the risk model might be related to the cell cycle, cytokine receptor interaction, and ATP synthesis coupled electron transport pathways. Moreover, the risk score showed significant positive correlation with CTLA4, while negative correlation with PD1. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) indicated the expression levels of EIF4EBP1 and UGDH were significantly higher in BRCA tissue compared with normal samples.
Conclusion
We identified two BRCA subtypes based on LRGs and constructed a risk model using five biomarkers. These findings may provide a theoretical basis and reference value for research and treatment in the direction of lysosomes in BRCA.